Effect of known polymorphisms on parasite biomass in severe malaria
James Watson
31/03/2022
Load data
Data are also saved as .csv files (one for the cases, one for the controls)
##
## FALSE TRUE
## 1500 698##
## FALSE TRUE
## 2184 14##
## FALSE TRUE
## 1825 373Compute endpoints
Compute hrp2/parasite ratio (in units of ng/parasite)
key polymorphisms
## The 14 polymorphisms we use in the analysis are:## [1] "hbb_rs334_num" "hba1_2"
## [3] "frem3_rs186873296_num" "abo_rs8176719_num"
## [5] "atp2b4_rs1541255_num" "g6pd_202"
## [7] "cd40lg_rs3092945_num" "rps6kl1_rs3742785_num"
## [9] "loc727982_rs1371478_num" "arl14_rs75731597_num"
## [11] "lphn2_rs72933304_num" "il10_rs1800890_num"
## [13] "cand1_rs10459266_num" "gnas_rs8386_num"Genotype frequencies
## hbb_rs334 frem3_rs186873296 abo_rs8176719 atp2b4_rs1541255 g6pd_202
## AA 96.9 89.1 47.0 45.4 74.0
## AT 2.6 10.6 44.2 46.3 13.8
## TT 0.5 0.2 8.8 8.3 12.2
## cd40lg_rs3092945 rps6kl1_rs3742785 loc727982_rs1371478 arl14_rs75731597
## AA 17.1 8.9 49.0 80.7
## AT 17.5 42.2 43.5 18.4
## TT 65.4 48.9 7.5 0.8
## lphn2_rs72933304 il10_rs1800890 cand1_rs10459266 gnas_rs8386 hba1_2
## AA 0.4 58.8 5.2 66.5 39.7
## AT 13.5 36.9 34.9 29.6 48.0
## TT 86.1 4.3 59.9 3.9 12.3## hbb_rs334 frem3_rs186873296 abo_rs8176719 atp2b4_rs1541255 g6pd_202
## AA 84.1 82 54.7 44.2 72.7
## AT 15.1 17 38.7 45.1 16.2
## TT 0.8 1 6.6 10.7 11.1
## cd40lg_rs3092945 rps6kl1_rs3742785 loc727982_rs1371478 arl14_rs75731597
## AA 13.3 9.6 54.3 84.7
## AT 16.4 38.3 37.5 14.4
## TT 70.3 52.1 8.2 1.0
## lphn2_rs72933304 il10_rs1800890 cand1_rs10459266 gnas_rs8386 hba1_2
## AA 0.7 57.5 4.8 65.4 34.4
## AT 15.7 36.0 32.4 31.4 49.5
## TT 83.6 6.5 62.8 3.2 16.1Case-only association study
Best fitting models. We use single imputation to which is best fitting model
## Across all imputations for log_parasites## HBB HBA1-2 FREM3 ABO ATP2B4 G6PD CD40LG
## imputation 1 "A" "R_nodiff" "A_nodiff" "R_nodiff" "A" "R_nodiff" "H_nodiff"
## imputation 2 "A" "R_nodiff" "A_nodiff" "R_nodiff" "A" "R_nodiff" "H_nodiff"
## imputation 3 "A" "R_nodiff" "A_nodiff" "R_nodiff" "A" "R_nodiff" "H_nodiff"
## imputation 4 "A" "R_nodiff" "A_nodiff" "R_nodiff" "A" "R_nodiff" "H_nodiff"
## imputation 5 "A" "R_nodiff" "A_nodiff" "R_nodiff" "A" "R_nodiff" "H_nodiff"
## imputation 6 "A" "R_nodiff" "A_nodiff" "R_nodiff" "A" "R_nodiff" "H_nodiff"
## imputation 7 "A" "R_nodiff" "A_nodiff" "R_nodiff" "A" "R_nodiff" "H_nodiff"
## imputation 8 "A" "R_nodiff" "A_nodiff" "R_nodiff" "A" "R_nodiff" "H_nodiff"
## imputation 9 "A" "R_nodiff" "A_nodiff" "R_nodiff" "A" "R_nodiff" "H_nodiff"
## imputation 10 "A" "R_nodiff" "A_nodiff" "R_nodiff" "A" "R_nodiff" "H_nodiff"
## RPS6KL1 LOC727982 ARL14 LPHN2 IL10 CAND1
## imputation 1 "H_nodiff" "R_nodiff" "A_nodiff" "H_nodiff" "A_nodiff" "A_nodiff"
## imputation 2 "H_nodiff" "R_nodiff" "A_nodiff" "H_nodiff" "A_nodiff" "A_nodiff"
## imputation 3 "H_nodiff" "R_nodiff" "A_nodiff" "H_nodiff" "A_nodiff" "A_nodiff"
## imputation 4 "H_nodiff" "R_nodiff" "A_nodiff" "H_nodiff" "A_nodiff" "A_nodiff"
## imputation 5 "H_nodiff" "R_nodiff" "A_nodiff" "H_nodiff" "A_nodiff" "A_nodiff"
## imputation 6 "H_nodiff" "R_nodiff" "A_nodiff" "H_nodiff" "A_nodiff" "A_nodiff"
## imputation 7 "H_nodiff" "R_nodiff" "A_nodiff" "H_nodiff" "A_nodiff" "A_nodiff"
## imputation 8 "H_nodiff" "R_nodiff" "A_nodiff" "H_nodiff" "A_nodiff" "A_nodiff"
## imputation 9 "H_nodiff" "R_nodiff" "A_nodiff" "H_nodiff" "A_nodiff" "A_nodiff"
## imputation 10 "H_nodiff" "R_nodiff" "A_nodiff" "H_nodiff" "A_nodiff" "A_nodiff"
## GNAS
## imputation 1 "H"
## imputation 2 "H"
## imputation 3 "H"
## imputation 4 "H"
## imputation 5 "H"
## imputation 6 "H"
## imputation 7 "H"
## imputation 8 "H"
## imputation 9 "H"
## imputation 10 "H"## Across all imputations for log_hrp2## HBB HBA1-2 FREM3 ABO ATP2B4 G6PD CD40LG RPS6KL1
## imputation 1 "A" "R" "A" "R" "R_nodiff" "H_nodiff" "H" "A_nodiff"
## imputation 2 "A" "R" "A" "R" "H_nodiff" "H_nodiff" "H_nodiff" "A_nodiff"
## imputation 3 "A" "R" "A" "R" "H_nodiff" "H_nodiff" "H_nodiff" "A_nodiff"
## imputation 4 "A" "R" "A" "R" "R_nodiff" "H_nodiff" "H_nodiff" "A_nodiff"
## imputation 5 "A" "R" "A" "R" "R_nodiff" "R_nodiff" "H_nodiff" "A_nodiff"
## imputation 6 "A" "R" "A" "R" "R_nodiff" "H_nodiff" "H_nodiff" "A_nodiff"
## imputation 7 "A" "R" "A" "R" "R_nodiff" "H_nodiff" "H_nodiff" "A_nodiff"
## imputation 8 "A" "R" "A" "R" "R_nodiff" "H_nodiff" "H_nodiff" "A_nodiff"
## imputation 9 "A" "R" "A" "R" "R_nodiff" "H_nodiff" "H_nodiff" "A_nodiff"
## imputation 10 "A" "R" "A" "R" "R_nodiff" "H_nodiff" "H_nodiff" "A_nodiff"
## LOC727982 ARL14 LPHN2 IL10 CAND1 GNAS
## imputation 1 "A_nodiff" "R_nodiff" "H_nodiff" "R_nodiff" "R_nodiff" "H_nodiff"
## imputation 2 "A_nodiff" "R_nodiff" "R_nodiff" "A_nodiff" "R_nodiff" "H_nodiff"
## imputation 3 "A_nodiff" "R_nodiff" "H_nodiff" "A_nodiff" "R_nodiff" "H_nodiff"
## imputation 4 "A_nodiff" "R_nodiff" "H_nodiff" "R_nodiff" "R_nodiff" "H_nodiff"
## imputation 5 "A_nodiff" "R_nodiff" "H_nodiff" "A_nodiff" "R_nodiff" "H_nodiff"
## imputation 6 "A_nodiff" "R_nodiff" "H_nodiff" "A_nodiff" "R_nodiff" "H_nodiff"
## imputation 7 "A_nodiff" "R_nodiff" "H_nodiff" "A_nodiff" "R_nodiff" "H_nodiff"
## imputation 8 "A_nodiff" "R_nodiff" "H_nodiff" "A_nodiff" "R_nodiff" "H_nodiff"
## imputation 9 "A_nodiff" "R_nodiff" "H_nodiff" "A_nodiff" "R_nodiff" "H_nodiff"
## imputation 10 "A_nodiff" "R_nodiff" "H_nodiff" "A_nodiff" "R_nodiff" "H_nodiff"## Across all imputations for log_ratio## HBB HBA1-2 FREM3 ABO ATP2B4 G6PD
## imputation 1 "R_nodiff" "R_nodiff" "A_nodiff" "R_nodiff" "R" "R_nodiff"
## imputation 2 "R_nodiff" "R_nodiff" "A_nodiff" "R_nodiff" "R" "R_nodiff"
## imputation 3 "R_nodiff" "R_nodiff" "A_nodiff" "R_nodiff" "R" "R_nodiff"
## imputation 4 "R_nodiff" "R_nodiff" "A_nodiff" "R_nodiff" "R" "R_nodiff"
## imputation 5 "R_nodiff" "R_nodiff" "A_nodiff" "R_nodiff" "R" "R_nodiff"
## imputation 6 "R_nodiff" "R_nodiff" "A_nodiff" "R_nodiff" "R" "R_nodiff"
## imputation 7 "R_nodiff" "R_nodiff" "A_nodiff" "R_nodiff" "R" "R_nodiff"
## imputation 8 "R_nodiff" "R_nodiff" "A_nodiff" "R_nodiff" "R" "R_nodiff"
## imputation 9 "R_nodiff" "R_nodiff" "A_nodiff" "R_nodiff" "R" "R_nodiff"
## imputation 10 "R_nodiff" "R_nodiff" "A_nodiff" "R_nodiff" "R" "R_nodiff"
## CD40LG RPS6KL1 LOC727982 ARL14 LPHN2 IL10
## imputation 1 "H_nodiff" "H_nodiff" "R_nodiff" "R_nodiff" "H_nodiff" "A_nodiff"
## imputation 2 "H_nodiff" "H_nodiff" "R_nodiff" "R_nodiff" "R_nodiff" "A_nodiff"
## imputation 3 "H_nodiff" "H_nodiff" "R_nodiff" "R_nodiff" "R_nodiff" "A_nodiff"
## imputation 4 "H_nodiff" "H_nodiff" "R_nodiff" "R_nodiff" "A_nodiff" "A_nodiff"
## imputation 5 "H_nodiff" "H_nodiff" "R_nodiff" "R_nodiff" "H_nodiff" "A_nodiff"
## imputation 6 "H_nodiff" "H_nodiff" "R_nodiff" "R_nodiff" "H_nodiff" "A_nodiff"
## imputation 7 "H_nodiff" "H_nodiff" "R_nodiff" "R_nodiff" "H_nodiff" "A_nodiff"
## imputation 8 "H_nodiff" "H_nodiff" "R_nodiff" "R_nodiff" "H_nodiff" "A_nodiff"
## imputation 9 "H_nodiff" "H_nodiff" "R_nodiff" "R_nodiff" "R_nodiff" "A_nodiff"
## imputation 10 "H_nodiff" "H_nodiff" "R_nodiff" "R_nodiff" "H_nodiff" "A_nodiff"
## CAND1 GNAS
## imputation 1 "A_nodiff" "H_nodiff"
## imputation 2 "A_nodiff" "H_nodiff"
## imputation 3 "A_nodiff" "H_nodiff"
## imputation 4 "A_nodiff" "H_nodiff"
## imputation 5 "A_nodiff" "H_nodiff"
## imputation 6 "A_nodiff" "H_nodiff"
## imputation 7 "A_nodiff" "H_nodiff"
## imputation 8 "A_nodiff" "H_nodiff"
## imputation 9 "A_nodiff" "H_nodiff"
## imputation 10 "A_nodiff" "H_nodiff"## HBB HBA1-2 FREM3 ABO ATP2B4 G6PD CD40LG
## "A" "R" "A" "R" "R_nodiff" "H_nodiff" "H"
## RPS6KL1 LOC727982 ARL14 LPHN2 IL10 CAND1 GNAS
## "A_nodiff" "A_nodiff" "R_nodiff" "H_nodiff" "R_nodiff" "R_nodiff" "H_nodiff"## [1] FALSECase-only analysis
Multiple imputation analysis
Estimate effects using multiple imputation - this is the main analysis underlying reported effects.
## ******* Analysis for hbb_rs334_num polymorphism
## For log_parasites model p=5.8e-07
## For log_hrp2 model p=3.64e-14
## For log_ratio model p=0.761
## ******* Analysis for hba1_2 polymorphism
## For log_parasites model p=0.672
## For log_hrp2 model p=0.00271
## For log_ratio model p=0.0802
## ******* Analysis for frem3_rs186873296_num polymorphism
## For log_parasites model p=0.21
## For log_hrp2 model p=0.00125
## For log_ratio model p=0.289
## ******* Analysis for abo_rs8176719_num polymorphism
## For log_parasites model p=0.0116
## For log_hrp2 model p=7.53e-09
## For log_ratio model p=0.113
## ******* Analysis for atp2b4_rs1541255_num polymorphism
## For log_parasites model p=0.0447
## For log_hrp2 model p=0.854
## For log_ratio model p=0.0283
## ******* Analysis for g6pd_202 polymorphism
## For log_parasites model p=0.322
## For log_hrp2 model p=0.846
## For log_ratio model p=0.248
## ******* Analysis for cd40lg_rs3092945_num polymorphism
## For log_parasites model p=0.45
## For log_hrp2 model p=0.0641
## For log_ratio model p=0.571
## ******* Analysis for rps6kl1_rs3742785_num polymorphism
## For log_parasites model p=0.97
## For log_hrp2 model p=0.102
## For log_ratio model p=0.223
## ******* Analysis for loc727982_rs1371478_num polymorphism
## For log_parasites model p=0.918
## For log_hrp2 model p=0.136
## For log_ratio model p=0.233
## ******* Analysis for arl14_rs75731597_num polymorphism
## For log_parasites model p=0.179
## For log_hrp2 model p=0.762
## For log_ratio model p=0.246
## ******* Analysis for lphn2_rs72933304_num polymorphism
## For log_parasites model p=0.945
## For log_hrp2 model p=0.959
## For log_ratio model p=0.974
## ******* Analysis for il10_rs1800890_num polymorphism
## For log_parasites model p=0.382
## For log_hrp2 model p=0.848
## For log_ratio model p=0.301
## ******* Analysis for cand1_rs10459266_num polymorphism
## For log_parasites model p=0.0417
## For log_hrp2 model p=0.356
## For log_ratio model p=0.157
## ******* Analysis for gnas_rs8386_num polymorphism
## For log_parasites model p=0.161
## For log_hrp2 model p=0.743
## For log_ratio model p=0.231## Effects for log_parasites
## Estimate upperCI lowerCI
## CD40LG (H) 1.10 0.86 1.40
## RPS6KL1 (A) 1.00 0.85 1.20
## LOC727982 (A) 0.99 0.85 1.20
## CAND1 (A) 1.20 1.00 1.40
## GNAS (A) 1.10 0.95 1.30
## ATP2B4 (A) 0.85 0.73 1.00
## G6PD (A) 0.93 0.81 1.10
## LPHN2 (A) 1.00 0.77 1.30
## IL10 (A) 1.10 0.91 1.30
## ARL14 (A) 0.85 0.67 1.10
## HBA1-2 (R) 0.94 0.69 1.30
## FREM3 (A) 0.82 0.60 1.10
## ABO (R) 0.78 0.64 0.95
## HBB (A) 0.31 0.20 0.49
## Effects for log_hrp2
## Estimate upperCI lowerCI
## CD40LG (H) 1.30 0.99 1.60
## RPS6KL1 (A) 1.10 0.97 1.30
## LOC727982 (A) 1.10 0.96 1.30
## CAND1 (A) 1.10 0.92 1.30
## GNAS (A) 1.00 0.87 1.20
## ATP2B4 (A) 1.00 0.87 1.20
## G6PD (A) 1.00 0.88 1.20
## LPHN2 (A) 1.00 0.77 1.30
## IL10 (A) 0.98 0.83 1.20
## ARL14 (A) 0.96 0.76 1.20
## HBA1-2 (R) 0.63 0.47 0.85
## FREM3 (A) 0.59 0.43 0.82
## ABO (R) 0.57 0.47 0.69
## HBB (A) 0.17 0.11 0.27
## Effects for log_ratio
## Estimate upperCI lowerCI
## CD40LG (H) 1.10 0.83 1.4
## RPS6KL1 (A) 1.10 0.94 1.3
## LOC727982 (A) 1.10 0.94 1.3
## CAND1 (A) 0.89 0.75 1.0
## GNAS (A) 0.90 0.76 1.1
## ATP2B4 (A) 1.20 1.00 1.4
## G6PD (A) 1.10 0.94 1.2
## LPHN2 (A) 1.00 0.76 1.3
## IL10 (A) 0.92 0.77 1.1
## ARL14 (A) 1.10 0.91 1.4
## HBA1-2 (R) 0.76 0.57 1.0
## FREM3 (A) 0.84 0.61 1.2
## ABO (R) 0.86 0.70 1.0
## HBB (A) 0.93 0.59 1.5Complete case analysis
## ******* Analysis for hbb_rs334_num polymorphism
## For log_parasites model p=6.09835421288473e-07
## For log_hrp2 model p=1.17530538078478e-10
## For log_ratio model p=0.258587493066735
## ******* Analysis for hba1_2 polymorphism
## For log_parasites model p=0.696438471095131
## For log_hrp2 model p=0.00031814351950014
## For log_ratio model p=0.00629041532293178
## ******* Analysis for frem3_rs186873296_num polymorphism
## For log_parasites model p=0.202043752475078
## For log_hrp2 model p=0.00483377488554595
## For log_ratio model p=0.644738841251556
## ******* Analysis for abo_rs8176719_num polymorphism
## For log_parasites model p=0.0131268621605838
## For log_hrp2 model p=7.94045743533939e-10
## For log_ratio model p=0.00789680319739409
## ******* Analysis for atp2b4_rs1541255_num polymorphism
## For log_parasites model p=0.0365547665148183
## For log_hrp2 model p=0.683465972091446
## For log_ratio model p=0.0227050400637977
## ******* Analysis for g6pd_202 polymorphism
## For log_parasites model p=0.334060332605031
## For log_hrp2 model p=0.392109058378897
## For log_ratio model p=0.451036782038497
## ******* Analysis for cd40lg_rs3092945_num polymorphism
## For log_parasites model p=0.45162926332164
## For log_hrp2 model p=0.0377943261243058
## For log_ratio model p=0.699784481657525
## ******* Analysis for rps6kl1_rs3742785_num polymorphism
## For log_parasites model p=0.917793585975565
## For log_hrp2 model p=0.316926457731408
## For log_ratio model p=0.401623870106487
## ******* Analysis for loc727982_rs1371478_num polymorphism
## For log_parasites model p=0.901025995467101
## For log_hrp2 model p=0.19524213647913
## For log_ratio model p=0.105254839058619
## ******* Analysis for arl14_rs75731597_num polymorphism
## For log_parasites model p=0.176876774434853
## For log_hrp2 model p=0.63689574957587
## For log_ratio model p=0.529945911503966
## ******* Analysis for lphn2_rs72933304_num polymorphism
## For log_parasites model p=0.877354000311971
## For log_hrp2 model p=0.926500884900159
## For log_ratio model p=0.644006985186236
## ******* Analysis for il10_rs1800890_num polymorphism
## For log_parasites model p=0.35520570614171
## For log_hrp2 model p=0.435214701782955
## For log_ratio model p=0.157306526974136
## ******* Analysis for cand1_rs10459266_num polymorphism
## For log_parasites model p=0.0501273145701642
## For log_hrp2 model p=0.231894440507826
## For log_ratio model p=0.168956190888501
## ******* Analysis for gnas_rs8386_num polymorphism
## For log_parasites model p=0.152117866523227
## For log_hrp2 model p=0.973668078126477
## For log_ratio model p=0.110265714565## Effects for log_parasites
## Estimate upperCI lowerCI
## CD40LG (H) 1.10 0.85 1.40
## RPS6KL1 (A) 0.99 0.85 1.20
## LOC727982 (A) 0.99 0.85 1.20
## CAND1 (A) 1.20 1.00 1.40
## GNAS (A) 1.10 0.95 1.40
## ATP2B4 (A) 0.85 0.73 0.99
## G6PD (A) 0.93 0.81 1.10
## LPHN2 (A) 1.00 0.78 1.30
## IL10 (A) 1.10 0.92 1.30
## ARL14 (A) 0.85 0.67 1.10
## HBA1-2 (R) 0.94 0.70 1.30
## FREM3 (A) 0.81 0.59 1.10
## ABO (R) 0.78 0.64 0.95
## HBB (A) 0.31 0.20 0.49
## Effects for log_hrp2
## Estimate upperCI lowerCI
## CD40LG (H) 1.40 1.00 1.90
## RPS6KL1 (A) 1.10 0.91 1.30
## LOC727982 (A) 1.10 0.94 1.40
## CAND1 (A) 1.10 0.92 1.40
## GNAS (A) 1.00 0.82 1.20
## ATP2B4 (A) 1.00 0.86 1.30
## G6PD (A) 0.93 0.78 1.10
## LPHN2 (A) 1.00 0.73 1.40
## IL10 (A) 1.10 0.89 1.30
## ARL14 (A) 0.93 0.70 1.20
## HBA1-2 (R) 0.52 0.36 0.74
## FREM3 (A) 0.57 0.39 0.84
## ABO (R) 0.48 0.38 0.61
## HBB (A) 0.18 0.10 0.30
## Effects for log_ratio
## Estimate upperCI lowerCI
## CD40LG (H) 1.10 0.78 1.40
## RPS6KL1 (A) 1.10 0.90 1.30
## LOC727982 (A) 1.20 0.97 1.40
## CAND1 (A) 0.87 0.71 1.10
## GNAS (A) 0.85 0.69 1.00
## ATP2B4 (A) 1.20 1.00 1.50
## G6PD (A) 1.10 0.90 1.30
## LPHN2 (A) 1.10 0.78 1.50
## IL10 (A) 0.86 0.71 1.10
## ARL14 (A) 1.10 0.82 1.50
## HBA1-2 (R) 0.61 0.43 0.87
## FREM3 (A) 0.91 0.62 1.30
## ABO (R) 0.73 0.58 0.92
## HBB (A) 0.73 0.43 1.30Estimate effects with additional adjustment for:
- age
- bacteraemia
- haemoglobin
## ******* Analysis for hbb_rs334_num polymorphism
## For log_parasites model p=1.54e-06
## For log_hrp2 model p=1.59e-17
## For log_ratio model p=0.567
## ******* Analysis for hba1_2 polymorphism
## For log_parasites model p=0.807
## For log_hrp2 model p=0.000731
## For log_ratio model p=0.0404
## ******* Analysis for frem3_rs186873296_num polymorphism
## For log_parasites model p=0.252
## For log_hrp2 model p=0.0034
## For log_ratio model p=0.435
## ******* Analysis for abo_rs8176719_num polymorphism
## For log_parasites model p=0.00874
## For log_hrp2 model p=4.05e-07
## For log_ratio model p=0.513
## ******* Analysis for atp2b4_rs1541255_num polymorphism
## For log_parasites model p=0.0633
## For log_hrp2 model p=0.345
## For log_ratio model p=0.00891
## ******* Analysis for g6pd_202 polymorphism
## For log_parasites model p=0.288
## For log_hrp2 model p=0.353
## For log_ratio model p=0.62
## ******* Analysis for cd40lg_rs3092945_num polymorphism
## For log_parasites model p=0.523
## For log_hrp2 model p=0.207
## For log_ratio model p=0.857
## ******* Analysis for rps6kl1_rs3742785_num polymorphism
## For log_parasites model p=0.964
## For log_hrp2 model p=0.864
## For log_ratio model p=0.869
## ******* Analysis for loc727982_rs1371478_num polymorphism
## For log_parasites model p=0.884
## For log_hrp2 model p=0.432
## For log_ratio model p=0.49
## ******* Analysis for arl14_rs75731597_num polymorphism
## For log_parasites model p=0.186
## For log_hrp2 model p=0.548
## For log_ratio model p=0.319
## ******* Analysis for lphn2_rs72933304_num polymorphism
## For log_parasites model p=0.974
## For log_hrp2 model p=0.845
## For log_ratio model p=0.922
## ******* Analysis for il10_rs1800890_num polymorphism
## For log_parasites model p=0.413
## For log_hrp2 model p=0.843
## For log_ratio model p=0.316
## ******* Analysis for cand1_rs10459266_num polymorphism
## For log_parasites model p=0.0421
## For log_hrp2 model p=0.544
## For log_ratio model p=0.0815
## ******* Analysis for gnas_rs8386_num polymorphism
## For log_parasites model p=0.339
## For log_hrp2 model p=0.952
## For log_ratio model p=0.291Figure 1 (main result)
Figure 1 (complete case)
Figure 1 (covariate adjusted)
Comparison complete case vs imputation
Type of model
Best fitting model for the main polymorphisms using complete data only
## [1] "hbb_rs334_num"
## Likelihood ratio test
##
## Model 1: log_hrp2 ~ g
## Model 2: log_hrp2 ~ g
## Model 3: log_hrp2 ~ g
## #Df LogLik Df Chisq Pr(>Chisq)
## 1 3 -1796.3
## 2 3 -1811.0 0 29.479 < 2.2e-16 ***
## 3 3 -1804.0 0 14.091 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## [1] "hba1_2"
## Likelihood ratio test
##
## Model 1: log_hrp2 ~ g
## Model 2: log_hrp2 ~ g
## Model 3: log_hrp2 ~ g
## #Df LogLik Df Chisq Pr(>Chisq)
## 1 3 -1762.6
## 2 3 -1761.1 0 2.9915 < 2.2e-16 ***
## 3 3 -1767.5 0 12.8384 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## [1] "frem3_rs186873296_num"
## Likelihood ratio test
##
## Model 1: log_hrp2 ~ g
## Model 2: log_hrp2 ~ g
## Model 3: log_hrp2 ~ g
## #Df LogLik Df Chisq Pr(>Chisq)
## 1 3 -1805.0
## 2 2 -1809.1 -1 8.1317 0.00435 **
## 3 3 -1805.0 1 8.1317 0.00435 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## [1] "abo_rs8176719_num"
## Likelihood ratio test
##
## Model 1: log_hrp2 ~ g
## Model 2: log_hrp2 ~ g
## Model 3: log_hrp2 ~ g
## #Df LogLik Df Chisq Pr(>Chisq)
## 1 3 -1813.2
## 2 3 -1809.3 0 7.7881 < 2.2e-16 ***
## 3 3 -1814.1 0 9.5403 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## [1] "atp2b4_rs1541255_num"
## Likelihood ratio test
##
## Model 1: log_hrp2 ~ g
## Model 2: log_hrp2 ~ g
## Model 3: log_hrp2 ~ g
## #Df LogLik Df Chisq Pr(>Chisq)
## 1 3 -1817.2
## 2 3 -1816.5 0 1.4114 < 2.2e-16 ***
## 3 3 -1816.9 0 0.7494 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Boxplots
Red cell polymorphisms
ATP2B4
Relationship with true severe malaria
data tilting case-control
## Doing hbb_rs334_num
## log10 weighted p-value is -31.0993176513668
## log10 non-weighted p-value is -37.7818996998084
## Doing hba1_2
## log10 weighted p-value is -5.52284974937648
## log10 non-weighted p-value is -4.16336276635852
## Doing frem3_rs186873296_num
## log10 weighted p-value is -12.1177869391016
## log10 non-weighted p-value is -10.9532600611397
## Doing abo_rs8176719_num
## log10 weighted p-value is -12.2596384157908
## log10 non-weighted p-value is -8.20013388974944
## Doing atp2b4_rs1541255_num
## log10 weighted p-value is -1.23471658484667
## log10 non-weighted p-value is -1.38527803603474
ATP2B4 and haemoglobin
